Voice Service System Adapting Response to Speaking Speed
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Solution Overview
Problem
Existing voice service technologies fail to accurately match voice responses with user demands due to ignoring the speed variations of speakers, leading to a poor match between the provided service and user needs.
Innovation Solution
A method and apparatus that analyze the time-domain waveform of voice input signals to determine current speaking speed, compare it with a user's standard speed information set, and generate a voice response signal based on the matched demand information, improving the match between voice service and user demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voice service technology converts voice signals into characters and analyzes them to determine response strategies, then the basic voice recognition function is achieved, but the potential demand information contained in different speaking speeds is ignored, leading to poor match between provided service and user demand
Solution Approach 1:
The patent segments the voice signal analysis into multiple dimensions: converting voice to text for semantic analysis, simultaneously extracting speaking speed from time-domain waveforms, and analyzing frequency-domain characteristics. This segmentation allows each aspect to be processed independently and then integrated to form a comprehensive understanding of user demand, resolving the contradiction between basic recognition accuracy and adaptability to user characteristics.
Solution Approach 2:
The patent changes the analysis parameters by not only converting voice to text but also extracting temporal parameters (speaking speed, pauses) and frequency parameters (pitch, tone) from the voice signal. By incorporating these additional parameters into the demand analysis, the system achieves both precise demand recognition and adaptability to individual user characteristics such as emotional state and speaking habits.
2Device complexity
If the system analyzes only the text content of voice signals, then the processing complexity is low, but the speaking speed information and emotional state information are lost
Solution Approach 1:
The patent merges multiple analysis approaches by combining text-based semantic analysis with waveform-based temporal and frequency analysis. The system processes voice signals through parallel pathways: one for text conversion and semantic understanding, another for time-domain waveform analysis to extract speaking speed, and a third for frequency-domain analysis to detect emotional tone. These merged results are then integrated to comprehensively determine user demand while maintaining manageable processing complexity through modular architecture.
3Productivity
If the voice service provides standardized responses, then the service delivery is efficient, but the responses do not adapt to different user emotional states and speaking speeds
Solution Approach 1:
The patent implements dynamic response adaptation by making the response generation process adjustable based on real-time analysis of user speaking speed and emotional state. The system dynamically selects from multiple response strategies: for fast speakers it may provide more concise responses, for slow speakers more detailed explanations; for excited emotional states it may use more energetic tone and shorter responses; for calm states it may provide more comprehensive information. This dynamic adaptation maintains service efficiency while significantly improving adaptability to user characteristics.
Solution Approach 2:
The system incorporates feedback mechanisms where the analyzed user characteristics (speaking speed, emotional state) feed into the response generation process. The response strategy is continuously adjusted based on this feedback loop, allowing the system to learn and adapt to individual user preferences over time while maintaining efficient service delivery through standardized response templates that can be dynamically modified.
Data Source
AI summary
The present disclosure discloses a method and apparatus for providing a voice service. A specific implementation of the method for providing a voice service comprises: acquiring a voice input signal; analyzing the time-domain waveform of the voice input signal to determine current speed information of the voice input signal; comparing the current speed information with an acquired standard speed information set of a user outputting the voice input signal, and determining first demand information from a preset demand information set according to the comparison result, wherein the standard speed information set comprises at least one piece of standard speed information, and the preset demand information set comprises demand information corresponding to each piece of standard speed information in the standard speed information set; and generating a voice response signal based on the first demand information and the second demand information acquired by analyzing the voice input signal.